Spillovers from Behavioral Interventions: Experimental Evidence from Water and Energy Use

This paper provides experimental evidence that behavioral interventions spill over to untreated sectors by altering consumer choice. We use a randomized controlled trial and high-frequency data to test the eect of social norms messaging about residential water use on electricity consumption. Messaging induces a 1.3 to 2.2% reduction in summertime electricity use. Empirical tests and household survey data support the hypothesis that this nudge alters electricity choices. An engineering simulation suggests that complementarities between appliances that use water and electricity can explain only 26% of the electricity reduction. Incorporating the cross-sectoral spillover increases the cost-eectiveness of the intervention by 62%

Utilities Included: Split Incentives in Commercial Electricity Contracts

The largest decile of commercial electricity customers comprises half of commercial sector electricity usage. We quantify a substantial split incentives problem that exists when these large firms are on electricity-included property lease contracts. Using exogenous variation in weather shocks, we show that customers on tenant-paid contracts use 6-14% less electricity in summer months. The policy implications are promising. Nationwide energy savings from aligning incentives for the largest 10% of commercial customers exceeds analogous savings from the entire residential electricity sector. It is also cost-effective: switching to tenant-paid contracts via sub-metering has a private payoff period of under one year

Final Report of the Information Technology Subcommittee for the Campus Master Plan

Through its work, data collection, outreach, and careful review of various studies and information, the committee is led to conclude that as it moves forward with implementation of its Master Plan, UMass Boston has a tremendous opportunity to plan for and design spaces that support and promote the learning, teaching, and research requirements of the campus community. It is hoped that the recommended guidelines and standards outlined in this report will assist and inform the planning and design of new and renovated campus facilities and specifically address the technological needs of classrooms, laboratories, offices, informal study areas, and social spaces throughout the campus. As technology transforms rapidly and the needs of the campus evolve, the committee also recommends that this report is reviewed and updated on a yearly basis

How to measure behavioural spillovers: a methodological review and checklist

A growing stream of literature at the interface between economics and psychology is currently investigating ‘behavioural spillovers’ in (and across) different domains, including health, environmental, and pro-social behaviours. A variety of empirical methods have been used to measure behavioural spillovers to date, from qualitative self-reports to statistical/econometric analyses, from online and lab experiments to field experiments. The aim of this paper is to critically review the main experimental and non-experimental methods to measure behavioural spillovers to date, and to discuss their methodological strengths and weaknesses. A consensus mixed-method approach is then discussed which uses between-subjects randomisation and behavioural observations together with qualitative self-reports in a longitudinal design in order to follow up subjects over time. In particular, participants to an experiment are randomly assigned to a treatment group where a behavioural intervention takes place to target behaviour 1, or to a control group where behaviour 1 takes place absent any behavioural intervention. A behavioural spillover is empirically identified as the effect of the behavioural intervention in the treatment group on a subsequent, not targeted, behaviour 2, compared to the corresponding change in behaviour 2 in the control group. Unexpected spillovers and additional insights (e.g., drivers, barriers, mechanisms) are elicited through analysis of qualitative data. In the spirit of the pre-analysis plan, a systematic checklist is finally proposed to guide researchers and policy- makers through the main stages and features of the study design in order to rigorously test and identify behavioural spillovers, and to favour transparency, replicability, and meta-analysis of studies